Triple
T33854581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saturn Award for Best Actress nomination for Natalie Portman |
E867735
|
entity |
| Predicate | recognizesGenre |
P133568
|
FINISHED |
| Object | science fiction film |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: science fiction film | Statement: [Saturn Award for Best Actress nomination for Natalie Portman, recognizesGenre, science fiction film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recognizesGenre Context triple: [Saturn Award for Best Actress nomination for Natalie Portman, recognizesGenre, science fiction film]
-
A.
analyzesGenre
Indicates that one entity examines or evaluates the genre characteristics or classification of another entity.
-
B.
genreOfRecognition
chosen
Indicates the specific genre or category in which an entity (such as a work or person) is formally recognized, honored, or awarded.
-
C.
genreRecognized
Indicates that a particular genre has been identified or acknowledged as applicable to an entity.
-
D.
commonGenre
Indicates that two entities share at least one genre in common.
-
E.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349943ccc8190a3c41a3e0ae46cbf |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: May 1, 2026, 1:47 a.m.